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Members:

Mario Obradović (manager and programmer)Filip Kontić (main programmer and researcher)Slobodan Dražić (researcher)Alexandrina-Lucica Romonti (documentation)Milenka Andjelic (documentation)

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Localization of the butterflySegmentation of the butterflyFinding the contoursClustering the contoursLearning the computer to recognize the class inwhich the butterfly belongs

Evaluation and results

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We used SVM (support vector machine) tolearn the computer to recognize in which classdoes the butterfly belong

Accuracy similar to some other butterflyclassification projects that can be found on theinternetResults:

On training images:

Class 1: 94.00%Class 2: 94.00%Class 3: 96.00%Class 4: 86.00%Class 5: 92.00%Class 6: 98.00%Class 7: 92.00%

Class 8: 96.00%Class 9: 94.00%Class 10: 90.00%----------------Total : 93.20%

Training+test data:

Class 1: 64.63%Class 2: 78.49%Class 3: 95.08%Class 4: 66.67%Class 5: 84.09%Class 6: 81.00%Class 7: 78.65%

Class 8: 92.73%Class 9: 84.44%Class 10: 64.29%----------------Total : 78.13%

Test:

Class 1: 31.25%Class 2: 62.79%Class 3: 90.91%Class 4: 45.00%Class 5: 73.68%Class 6: 74.00%Class 7: 58.97%

Class 8: 60.00%Class 9: 65.00%Class 10: 23.53%----------------Total : 57.23%

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Similar classes (2 and 7, 5 and 10, 1 and fewothers)Different stance of the butterfly (etc. spreadwings, different angles...)Not enough butterflys for training, smalldatabase

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